Building MongoDB's Complex Go-to-Market Motion with Meghan Gill

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This is a podcast episode titled, Building MongoDB's Complex Go-to-Market Motion with Meghan Gill. The summary for this episode is: <p>Hypergrowth organizations are constantly evolving: product offerings change, go-to-market strategies shift, personnel turns over.</p><p><br></p><p>In Operations, we often have to help our companies through those seismic shifts. On this episode, we're talking to someone who has seen 12 years of those shifts at her company and now oversees one of the more complex go-to-market motions we’ve ever talked about on this show.</p><p><br></p><p>Our guest, Meghan Gill, is the VP Sales Operations and Sales Development at MongoDB, the database platform company that went public in 2017.</p><p><br></p><p>In our conversation, we talk about the evolution of the go-to-market motion Meghan has overseen at MongoDB, particularly their transition to to pay-as-you-go pricing, how to forecast a consumption based business, and what it means to have "smokey" accounts in MongoDB’s territory planning process.</p><p><br></p><p>Like this episode? Be sure to leave a ⭐️⭐️⭐️⭐️⭐️⭐️&nbsp;review and share the pod with your friends! You can connect with Sean and Meghan on Twitter @Seany_Biz, @meghanpgill, and @DriftPodcasts.</p>

Sean Lane: (singing). Hey, everyone. Welcome to Operations, the show where we look under the hood of companies in hypergrowth. My name is Sean Lane. Something that's always been incredible to me is the ability for organizations to morph and evolve over time. That company that you just joined a few years ago may look nothing like the one you work at today. Product offerings change, go- to- market strategies shift, personnel turns over, and in operations, you often have to help your organization through these seismic shifts. How you motivate and incentivize people changes, how you find signals of success within your customer base changes. I've wondered sometimes whether institutional knowledge is a blessing or a curse in hypergrowth companies. You're blessed with the knowledge of context and understanding of why things worked or didn't work, but you're also cursed by the biases that these experiences and this context brings on your current and future decisions. Now, how about someone with 12 years worth of institutional knowledge inside of hypergrowth, along with a complex, ever- evolving go- to- market motion that spans across multiple products and a handful of different sales motions? That's what our guest today, Meghan Gill, brings to our conversation. Meghan is the VP of sales operations and sales development at MongoDB, the database platform company with over 29,000 customers that's been downloaded over 200 million times and went public in 2017. Since joining the company back in 2009, Meghan has risen through the ranks and she now oversees one of the more complex go- to- market motions that we've ever talked about on this show. In our conversation, we're going to talk about the evolution that Meghan has overseen at MongoDB, particularly their transition to pay- as- you- go pricing, how to forecast a consumption- based business, and what it means to have smoky accounts in MongoDB's territory planning process. Let's start though, with hearing from Meghan about those different components of the complex go- to- market at MongoDB and the role her team plays in these different motions.

Meghan Gill: So I run sales operations and strategy, and we have a pretty complicated go- to- market, so we have an on- prem product as well as a cloud- based product. And the cloud- based product is consumption- based, so customers can pay as they go, kind of like the way you would pay for your electricity bill. And then in terms of the different channels we have, we have a self- serve channel, so any software developer that wants to use MongoDB can rock up to our website with their credit card and start paying for MongoDB on their own. We also have a high velocity inside sales team, which is a more junior sales rep, and they're primarily working with customers that have somehow engaged with us, typically through our self- serve channel. We have your traditional enterprise sales force, which is globally distributed, working with customers out in the field, and then we also have a partner channel. So it certainly has many different layers, four different channels on- prem and cloud, all in one go- to- market, so it keeps my job very interesting.

Sean Lane: I would imagine. You've been with the company for quite some time. Has each one of those different go- to- market motions developed at different points in the company's maturity?

Meghan Gill: Yeah, it's interesting how MongoDB has evolved over time. So I joined coming up on 12 years ago, so I like to tell people I joined when I was 14, but when I joined, we were solely focused on... MongoDB inaudible... It's an open- source database technology. We did not have a commercial version. Any software developer could download and get started with MongoDB for free. And then the first commercial product we offered was a... Well, first, we offered just straight support, and then we built a set of on- prem tooling around MongoDB, which we called MongoDB Enterprise Advanced. So our first iteration of go- to- market was very, your traditional software sale. And then about five years ago, and in fact, I'm wearing my fifth- anniversary t- shirt of MongoDB Atlas, which is our cloud product, was launched, and that was when we introduced the self- serve channel. And that's really when the go- to- market started getting pretty complex because now we had not just software engineers downloading and playing with the product, but people actually paying on a credit card and using it, becoming customers without ever engaging with a sales rep.

Sean Lane: And so, one of the reasons I ask about that is, I would have to imagine that your level of predictability for the stuff that was there when you started when you were 14 versus the stuff that's only five years old now as a product, that must be very different for you from an ops perspective, in terms of looking at the funnel metrics, the predictability, how you forecast, how you think about each of those business units, or am I totally wrong and you've got the whole thing nailed down?

Meghan Gill: Well, it's definitely an evolution, so I'll give you an example. In a traditional bookings- based model, you could easily tell a rep," Well, you need to generate X dollars of qualified pipeline to hit your target and we're going to hold you accountable to that." And we built a bunch of dashboards around leading indicators called metrics for success to track the reps against that. Now, we move into a majority consumption- based model where a rep can close a deal with no commitment upfront and all the bookings happen afterwards. And how do I hold them accountable to generating pipeline when they're closing opportunities that have no upfront commit and the consumption happens over time? And that is an ongoing challenge for us when it comes to evolving our go- to- market.

Sean Lane: Okay. Let's make sure we're all following along with this complex setup at MongoDB. You've got two different products, one on- prem and one cloud- based, and then four different go- to- market sales motions, a self- serve, a high- velocity inside sales model, an enterprise model, and a channel model. Now, when it comes to defining these metrics for success that Meghan is describing, that sounds really challenging when you have consumption- based opportunities. What do you do when you have no upfront commitment, when you don't have a real opportunity value to put onto your deal, when you don't have a traditional pipeline target to go after in the first place? How do I plan ahead, as a rep, in that situation, and how do I, as sales ops, help the reps on my team to know whether or not they're on track to hit their goals?

Meghan Gill: Yeah, I mean, now, the simple first iteration is that we are starting to think less about the dollar value of the opportunity and more about the volume of opportunities that the rep is driving, or the number of new workloads they're potentially driving. But then this all has ramifications across not just the sales reps, but all the supporting functions. So I also have the sales development team, for example, rolling up to me, and they have been laser- focused on generating qualified pipeline. So now, they're like," Well, our qualified pipeline numbers are... Is that even the right number for us to be focused on? Should we be focused on the number of opportunities that we're able to generate?" Similar for marketing. Marketing- sourced bookings, is that the right metric to measure marketing on? So it starts to become a question for all the other teams as well.

Sean Lane: Yeah, that's super interesting. So I'm trying to think to your point about these ripple effects across different parts of the business, as you guys are making this switch to the consumption- based model. And one of the areas that I can imagine it has a huge ripple effect on is compensation, and so with both the complexity of the different four go- to- market motions and the on- prem versus cloud version of your product, there must be a lot of complexity in how you think about both the design of the comp plans and how you think about the types of behaviors you're trying to incentivize with your team.

Meghan Gill: Yeah, the first challenge we had as we were trying to shift the sales force to our cloud- based product, the first iteration, we were basically selling commitments. Go and get your customer to commit to, say, buy a hundred dollars of MongoDB Atlas. And this had a few issues. The first issue is that all of the cloud providers, AWS and Google and Microsoft Azure, they've all conditioned customers to want to pay as you go, so customers would be pushing back. Secondly, it was slowing down sales cycles because for example, if it's a new application, we're having to go bring in a sales engineer, do a complicated sizing exercise to estimate how much the customer might spend. So it's as if your electricity company, your utility provider would come to you at the beginning of the year and say," How much are you going to spend on electricity?" And you're like," I don't know. How hot is it going to be this summer?" And it's really impossible to guess. So we rolled out elastic invoicing, which is our version of pay as you go, but there was this inherent bias towards doing the commits because, well, that's immediately going to retire my quota. What we wanted to do was try to find a way to neutralize whether a customer wants to buy on- prem, commit, or pay as you go. How do we make it all even? So what we decided to do is pay the reps and measure the reps for customers that are in the pay- as- you- go or elastic invoicing model, that they would get measured on the run rate of that customer at the end of the quarter. And in terms of implementing it, so the rep can close an opportunity at, say,$ 0, and then we automatically spin off what we call a run rate opportunity in Salesforce, and that updates every day with the consumption. And then it closes at the end of the quarter so that it can be tracking the consumption of that customer over time, and then that makes it as attractive to close a no- commit customer as a commit customer or even an on- prem customer.

Sean Lane: Because I would imagine if I'm the rep, trying to think about the pros and cons of those three, the on-prem, the commit, and the pay as you go, certainly, some of that's going to be driven by the customer's expectations and what their goals are, but they're also, in the back of their minds, thinking about how this is going to impact the comp plan, right? How do you help them to both understand and still want to do what's best for the customer at the end of the day between these different plans, because I would imagine that's a tough conversation, to always end up with the right outcome for the customer and not just based on what the comp plan is?

Meghan Gill: We're constantly thinking about, what's the right balance? I think initially, it took some time just for the reps to wrap their head around the concept of getting paid on consumption. We had to do a ton of enablement around that. And we, obviously, pitched it as a huge benefit, right? It's meant to reduce friction with customers, it's meant to drive velocity, make it easier for reps to get a customer started. We showed them data that once a customer starts using Atlas, our cloud product, it's likely that they're going to grow and that it's very, very sticking. So that was for the initial rollout, and then what happened was, a few teams started having a lot of success with it. And that's, of course, when things really began to take off and it became common throughout the work.

Sean Lane: Let's pause here because this structure is super impressive, both from a system architecture perspective, as well as a change management perspective. After that initial pay- as- you- go opportunity is closed, Meghan's team is tracking consumption on a daily basis and then closing out subsequent opportunities on a quarterly basis, and that's how the reps ultimately get paid. I know firsthand that communicating any sort of comp plan, no matter how simple it is, can be an important and challenging task. And with all of this nuance, Meghan and her team leaned onto the social proof that the peers of some of the people on the team were succeeding to help them spread the word about this model. I also think that the reps themselves started to see the upside of this consumption- based model. If we go back to the electricity bill example, what if that new customer that you just signed, all of a sudden, turns on their air conditioning for 24 hours a day, all summer long? The deal you signed just got a lot bigger. And according to Meghan, this type of model also drove more cross- functional collaboration amongst the teams because every moment, there was an opportunity to potentially upsell that customer, as well as potentially churn that customer. Now, with all this volatility, though, as an ops person, I couldn't help but think about how hard it must be to forecast this type of business, so I asked her," Meghan, how do you and your team do it?"

Meghan Gill: I wish I could say we had this completely figured out. I mean, if anything, I actually think the run rate customers are a little bit easier to predict, right, because we're looking at how much they consumed over the last 90 days. As we get closer to the end of the quarter, that just converges with the actuals, whereas in the bookings model, it's very binary. Did we get the deal? Did we not get the deal? So at the beginning of the quarter, it's usually a question of, will that customer expand and bring on new applications that will significantly increase their consumption? But over the broad portfolio, at the level I'm looking, which is typically at the SVP or the CRO level, it tends to be a little bit more predictable than the booking side of the house.

Sean Lane: And so, you basically, I would imagine then, have to basically end up with three different forecast models, one for on-prem, one for the bookings, and one for their consumption?

Meghan Gill: We have, one, well, one consolidated forecast, but typically, the way the leaders think about it, they say," Well, I have this much in run rate. I can expect it to grow because historically, it grows a certain amount," and that's kind of in the bag, right, because they're already consuming. And then there's a set of booking steals where we're like," Well, these are pretty likely to happen," and then you have, how much of the rest of it is... What's your upside? So it's slightly different way of forecasting because you have to think about multiple different variables. But yeah, I would say a lot of the sales leaders, they tell me that end of quarter is not quite as exciting as it was in previous iterations of MongoDB or in other companies because by the end of the quarter, a lot of the elastic run rate deals, which are often the big deals, have already been accounted for.

Sean Lane: From a predictability standpoint, that sounds lovely to me. That sounds great as opposed to hoping that the person's wifi from their vacation house allows them to sign the DocuSign on the last day of the quarter. That sounds much better to me. Do-

Meghan Gill: I guess the counter to that though, is that if you're looking at your annual number, then you have to be more strategic. At the beginning of the year, how many new logos am I going to get onboard that will ramp up consumption over the course of the year? And it's definitely a completely different mindset.

Sean Lane: So let's talk more about that, right, because that's, I think, one of the other big ripple effects, right, which is how you all look at those existing customers and the signals that you use to identify that hopeful future consumption, increase, future expansion, whatever you call it. One of the things you were telling me about is that you all at MongoDB have, very purposefully, made it very seamless for people to be able to use the product without really giving you a whole lot of information. And so, I'm curious about the trade- offs there, about how you acquire those customers in the first place versus that annual dilemma that you're describing of having to actually understand what the growth of existing customers might look like.

Meghan Gill: Sure, yeah. So if we rewind, back when I was 14 and started at MongoDB, the founders took a very developer- focused approach and they wanted to have as little friction as possible for an individual software developer to get started with MongoDB, and that meant that downloading MongoDB had to be super easy. You had to be able to get it started and installing and experiencing the magic of MongoDB within five minutes, so that means we don't collect any information upon download of the open- source version. And when we started building a sales and marketing team, many of the salespeople were baffled. They were like," Oh my gosh, there are people out in the wild using our product in production and we don't know who they are." But that was a really deliberate trade- off because we felt, in order to capture the massive database market, we needed to have as much adoption from developers as possible. So you fast forward to today and designing territories and finding the accounts that we think have the highest propensity is a big part of what the sales ops function does, and so we look at a bunch of different signals. Some of the signals are internal ones like, are they active on our website, are they doing different activities, attending events, being part of our online MongoDB University platform? Some of them are product signals like, hey, do we have developers using the free tier or the paid tier? Some of them are external signals like, do they have a MongoDB job listed on their website or do they have people with MongoDB skills on their LinkedIn profiles? And we took all of that data and we actually built an internal application to bring all that data together and present it to the sales leaders in a very simple format so that they could design territories and focus their sales reps on the accounts that have the highest propensity at buy.

Sean Lane: So I want to focus on the very last thing you just said there, which was, so that they, the sales leaders, can design these territories. And so, this is always a very interesting dynamic in different companies, how sales ops partners with sales leaders to actually get those territories in the hands of the reps. And so, in this scenario where you all have built something internally using your own tool to bring those things together, can you take me through what you're actually delivering to them and then what they're taking and doing with that information?

Meghan Gill: Yeah, sure. And by the way, I should mention, we built it on MongoDB, of course, little plug for our product. So I would add that it also varies by segment, so this application that we built internally, which we call Argus, and I cannot remember... I think it's some Greek mythological creature with a lot of eyes. And the idea is that we're giving the sales team visibility into all of this data in a single place, and so bringing together the data from both... matching up the data from Salesforce, from our product, and from these external data sources, was a constant challenge. So that was challenge number one, how do we map and integrate all the data? And then the second challenge was presenting it in a way that the sales leaders could more easily understand. A simple example is, if you build a Salesforce report, it's like, I can build it by parent account or I can build it by the child accounts. If I build it by parent, it's way too course. If I build it by child, it's way too granular and it's too much data for the leaders to work with. So being able to display the data to nest the sub- accounts, to give the sales leaders the opportunity to flag accounts that they think have potential, that they think have what we call smoke, as in, where there's smoke, there's fire, so they can tag accounts as smoky, that is like they're actually contributing to the data that we're using to decide how to build territories. The other thing I'll say is that territory design is quite different for our enterprise team, which is our field team versus our inside sales team, which we call our corporate team. The enterprise team, it's more of an art than a science, right? I don't think that that territory management is something that can come centrally from sales ops because we have some accounts where we have a single rep assigned to that account. And it's all about the relationship the rep has, the skillset the rep has, and the manager really has the best insight into the people on the accounts and how to match them up appropriately. And our inside sales team, which is much more high velocity and transactional, they're primarily focused on taking companies with strong signal of already using MongoDB, through all of that data that we have, and converting them and getting them onto an elastic invoicing contract. So in that world, you can almost think of an account as like a commodity. And it's like, how many do we have? Let's make sure we get as many into the hands of our reps as possible. And we've built a pretty good machine around that, where we come up with a list of accounts that we think look feasible. We have a BDR research team based in India that does a bunch of data scrubs to review whether or not those accounts meet certain criteria and do a little bit of manual research on them. Then those go into what we call the bullpen, so it's a territory where it's a holding place for accounts, and as people either disqualify accounts or we hire new reps, we pull from the bullpen to top them up.

Sean Lane: Okay, so I obviously looked it up and Argus is, in fact, a many- eyed monster from Greek mythology. In fact, his full name, Argus Panoptes, translates to all- seeing. And Meghan may have glossed over this part a little bit, but the amount of work and disparate data sources that were required to pull something like Argus together was no small feat. I also absolutely love how they call the accounts that are showing signs of buying as" smoky." It's just so good. Okay, anyways, getting back to what she said, the distinction that Meghan made between the different segments is a really important one. If you're running a more enterprise- style go- to- market motion, you probably want to follow her advice that sometimes, territory planning is going to be little heavier on the art and not just the science. Meanwhile, if you have a shorter, more transactional sales motion or an inside sales motion, that's probably where signals provided by something like Argus are going to be really strong indicators of success. And this last part got me thinking, does that mean that the majority of accounts going into the MongoDB territories have some kind of smoke signal already, or do they still have a true net new motion in their territories as well?

Meghan Gill: Ideally, we have a little bit of a blend, right, where you have some existing customers that you can have some opportunity to upsell, some smoky accounts, and some real, true, hard- headed, or greenfield accounts. The other thing that I think about is the incentives because if I'm a rep, it's always easier for me to go and expand or milk my existing accounts or go after the lower- hanging fruit. Salespeople are like water, right? They flow to the path of least resistance, which is the right thing to do. But if we really want to try to expand market share, you have to make sure we have the right incentives in place. So in addition to finding them the right accounts, we also have incentives around new logos, whether it's bonuses, spiffs, gates to accelerate, or things like that, to make sure that we're not neglecting the accounts that could have potential, but don't necessarily have signal at this exact moment.

Sean Lane: Got it. That makes total sense, and so almost stratifying the incentives to continue to expand that market share. On the signals themselves, right, whether it's that initial pass, the pass that you're doing with the BDRs, what good looks like, or what the right smoke signals are, I would have to imagine took some time to land on, in the first place. And is that something that you're still constantly evolving, or how do you know what the right signals are?

Meghan Gill: Yeah. I mean, I think we have a pretty good idea of what the low- hanging fruit is. If somebody is hiring MongoDB developers and they're using the free tier of Atlas, that's a pretty hot account. I think what's probably harder is the accounts that are, say, tech- forward or digital natives that may not actually be actively engaged with MongoDB. How do we decide which of those to prioritize and where is the biggest opportunity? So I would say on the low- hanging fruit side, I think we probably have a pretty good process, but I think it's still an evolution to figure out, which are the right greenfield accounts for us to go after?

Sean Lane: And to your point, I could also see that being more of that art conversation in the enterprise, right, like, do we have reps that have relationships here, do we have a rep that's been in this vertical or this industry before? And I think that's probably the biggest pro of putting the managers a little bit more in a powerful position when it comes to carving the territories, is that fair?

Meghan Gill: It is, and it also enables the managers to encourage... It's a way for them to reward the best reps and create a culture of meritocracy. So if you're a rep that's doing the right things, then you're going to get the next hot account or inbound lead.

Sean Lane: Yeah. And I would also have to imagine it's less of like, oh, this is the territory that I got from the company, or this is the territory I got from ops. It puts a little bit more ownership on the team itself.

Meghan Gill: That is definitely the case. And the other nice thing about that is that it's because the managers have to look at this data and make decisions, they are also able to go to the reps and say," These are the accounts I'm giving to you and here's why I'm giving them to you." And then the reps also have access to Argus, which is a tool that we built, and they use those signals to figure out, how am I going to pipeline generate into that account? Like," Hey, we gave you this account because we see that they have a bunch of developers using the free tier," That's going to be very different from," We're giving you this account because we see that they are building their own software, they're digital native, they're in the cloud, they're a big AWS customer," right? The approach might be different.

Sean Lane: And to bring things back to the very beginning of our conversation, I would also imagine that that helps the rep do that planning that we were talking about, right, of understanding, on the consumption- based accounts, how much of my quota we anticipate to be taking care of from these existing accounts and their growth, versus the ones that I need to go out and basically generate that myself to close the rest of the gap. Is that how they do that planning, there's a little bit of consumption- based assumptions and then those net new accounts as well?

Meghan Gill: Yeah, and I think they do. And they do an exercise on their path to money or route to money based on the accounts that they have and how they're going to prospect into those accounts, so we have a bunch of templates in terms of how... basically, walking them backwards in terms of, what do you want to achieve, okay, then what do you need to do in order to get to that end goal?

Sean Lane: Before we go, at the end of each episode, we're going to ask each guest the same lightning round of questions. Ready? Here we go. Best book you've read in the last six months?

Meghan Gill: Whoa, best book I've read in the last six months. Well, I recently re- read the Oh Crap! Potty Training book. Does that count?

Sean Lane: I was going to say, I know you have two young kids, so children's books absolutely qualify.

Meghan Gill: Okay, but I should at least come up with a good business book, right? I recently also re- read Crucial Conversations, which is a great book about having difficult conversations, so if you're looking for a business book, that's the one I would recommend.

Sean Lane: We'll take them both, we'll take them both. Favorite part about working in ops?

Meghan Gill: Getting to solve lots of different kinds of interesting problems.

Sean Lane: Least favorite part about working in ops?

Meghan Gill: End- of- quarter fire drills. Those are probably my least favorite. But truthfully, I also enjoy those because they're also typically interesting problems that I need to solve.

Sean Lane: I can strangely identify with that, right? It's like, oh, here's another one, but I kind of love it, in a weird, chaotic way.

Meghan Gill: It's satisfying to fix something, for sure.

Sean Lane: Of course, of course. Someone who impacted you getting to the job you have today?

Meghan Gill: Well, it'd have to be the CEO of MongoDB, David Ittycheria, who said," Hey, why don't you take over sales ops?" And I was like," Sales ops?" I'd never seen a comp plan before. And I asked around a few people, including a pretty good friend of mine, Giuseppe, who's now the CEO of a company called Sitetracker, and I said," Do you think I should take this job?" And because he had been head of sales ops at MongoDB before he went to take the CEO route, he's like," You're going to be spending 50% of your time on sales comp." And I remember thinking to myself," There can't be that much in sales comp," but little did I know. But yeah, so I definitely have to shout out Dev for thinking that I could do this job, coming from marketing. And then the other person would be when I joined, again, when I was 14- years- old, was the founder of MongoDB who took a chance on me and said," Oh, you're smart. You'll be able to make an impact here."

Sean Lane: That's amazing. All right, last one, one piece of advice for people who want to have your job someday?

Meghan Gill: This is not my quote, I think it's a Sheryl Sandberg quote, but when someone asks you to join a rocket ship, you don't say," What seat?" You just get on. So my advice to people who want to have amazing careers is, focus on being at the right companies because if you're in a company with great people, great culture, that's growing fast, there will always be opportunities to learn new things, try new things. I never would have guessed that I would be running sales ops at MongoDB, but because I was in this fast- growing company, this opportunity presented itself. So that would be my number one piece of advice.

Sean Lane: I feel like that's such a healthy perspective too, in an industry like ours, where people jump around quite a bit and you are just seeking out that next opportunity, even if it's within the four walls of the place where you currently are, as opposed to thinking that that thing has to be outside of where you're currently at.

Meghan Gill: Yeah, I think that is true. I've seen people chase a title or chase a role and go work at a company that's, frankly, not that great, and realize, well, being VP of X at a company that's not going anywhere is not as good as being a senior IC at a company that's a rocket ship. And I think the reason Sheryl Sandberg is a good example of that is, she could be CEO of so many Silicon Valley companies, clearly, but she's COO of Facebook and she's probably having a bigger impact in that role than she could being CEO of another company. So that's my advice, pick the right company.

Sean Lane: I love it. Meghan, thank you so much for doing this. I really appreciate you taking the time.

Meghan Gill: Thank you. The last thing I'm going to say is that I'm hiring. I have lots of open roles, so if you're interested in solving some of these problems, shoot me an email. It's just Meghan at MongoDB.

Sean Lane: Perfect, love it. Connect with Meghan on LinkedIn, apply for some of her gigs. Thanks, Meghan. Thank you so much to Meghan Gill for joining us on this week's episode of Operations. If you want to follow up with Meghan on some of those jobs that she was talking about, head to mongodb. com/ careers, mongodb. com/ careers. If you liked what you heard today, make sure you're subscribed so you get a new episode of Operations into your feed every other Friday. And if you feel like you learned something today, do us a favor, leave us a six- star review on Apple Podcasts or wherever you get your podcasts, six- star reviews only. All right, that's going to do it for me. Thanks so much for listening. We'll see you next time.( singing).

DESCRIPTION

Hypergrowth organizations are constantly evolving: product offerings change, go-to-market strategies shift, personnel turns over.

In Operations, we often have to help our companies through those seismic shifts.

So in this episode, we talk to Meghan Gill, VP of Sales Operations and Sales Development at MongoDB.

Meghan has seen 12 years of those shifts at her company and now oversees one of the more complex go-to-market motions we’ve ever talked about on this show.

You'll learn:

  • What go-to-market structure looks like at MongoDB & how it’s changed over Meghan’s tenure (2:24)
  • How MongoDB's operations team defines success and aligns with sales on metrics (7:00)
  • The behaviors that influence MongoDB's compensation plans (8:00)
  • How MongoDB forecasts a consumption-based model (13:30)
  • The balance of measuring both net-new customer acquisition and annual customer growth (16:20)
  • The importance of transparency between operations and sales teams (19:30)
  • What net-new vs. old smoke signals mean for MongoDB's database (23:55)
  • How MongoDB defines a "good" account (25:25)